Abstract

Collaborative Learning Flow Patterns (e.g., Jigsaw) offer sound pedagogical strategies to foster fruitful social interactions among learners. The pedagogy behind the patterns involves a set of intrinsic constraints that need to be considered when orchestrating the learning flow. These constraints relate to the organization of the flow (e.g., Jigsaw pattern - a global problem is divided into sub-problems and a constraint is that there need to be at least one expert group working on each sub-problem) and group formation policies (e.g., groups solving the global problem need to have at least one member coming from a different previous expert group). Besides, characteristics of specific learning situations such as learners’ profile and technological tools used provide additional parameters that can be considered as context-related extrinsic constraints relevant to the orchestration (e.g., heterogeneous groups depending on experience or interests). This paper proposes a constraint framework that considers different constraints for orchestration services enabling adaptive computation of orchestration aspects. Substantiation of the framework with a case study demonstrated the feasibility, usefulness and the expressiveness of the framework.

Sinha, T.: Together we stand, together we fall, together we win: dynamic team formation in massive open online courses. In: Fifth International Conference on the Applications of Digital Information and Web Technologies, pp. 107–112 (2014)

16.

Inaba, T., Ando, K.: Development and assessment of CSCL system for large classrooms using collaborative script. In: eLmL 2014: The Sixth International Conference on Mobile, Hybrid and Online Learning, Spain, pp. 14–21 (2014)